UC Berkeley

Since tens of thousands of nanoporous materials have been synthesized and millions have been hypothesized, our ability to both predict novel materials and their performance for a given application in a computational setting is becoming increasingly important. Utilizing simulations that can screen for optimal material performance becomes invaluable since exhaustive experimental exploration of this vast chemical space can quickly become experimentally intractable from an expense and time efficiency standpoint. This thesis is therefore dedicated to advancing the computational tools and algorithms that can be used to both predict novel materials and evaluate their performance for clean energy technologies.